Profiling Cookbook¶
The section contains examples how to perform CPU profiling for Apache DataFusion on different operating systems.
Building a flame graph¶
Video: how to CPU profile DataFusion with a Flamegraph
A flamegraph is a visual representation of which functions are being run You can create flamegraphs in many ways; The instructions below are for cargo-flamegraph which results in images such as this:
MacOS¶
Step 1: Install the flamegraph Tool¶
To install flamegraph, run:
cargo install flamegraph
Step 2: Prepare Your Environment¶
Ensure that you’re in the directory containing the necessary data files for your DataFusion query. The flamegraph tool will profile the execution of your query against this data.
Step 3: Running the Flamegraph Tool¶
To generate a flamegraph, you’ll need to use the – separator to pass arguments to the binary you’re profiling. For datafusion-cli, you need to make sure to run the command with sudo permissions (especially on macOS, where DTrace requires elevated privileges).
Here is a general example:
sudo flamegraph -- datafusion-cli -f <path_to_sql_file/sql_file.sql>
Example: Generating a Flamegraph for a Specific Query¶
Here is an example using 28.sql:
sudo flamegraph -- datafusion-cli -f 28.sql
You can also invoke the flamegraph tool with cargo to profile a specific test or benchmark.
Example: Flamegraph for a specific test:¶
CARGO_PROFILE_RELEASE_DEBUG=true cargo flamegraph --root --unit-test datafusion -- dataframe::tests::test_array_agg
Example: Flamegraph for a benchmark¶
CARGO_PROFILE_RELEASE_DEBUG=true cargo flamegraph --root --bench sql_planner -- --bench
CPU profiling with XCode Instruments¶
Profiling using Samply cross platform profiler¶
There is an opportunity to build flamegraphs, call trees and stack charts on any platform using Samply
Install Samply profiler
cargo install --locked samply
More Samply installation options
Run the profiler
samply record --profile profiling ./my-application my-arguments
Profile the benchmark¶
Set up benchmarks if not yet done
Example: Profile Q22 query from TPC-H benchmark.
Note: --profile profiling to profile release optimized artifact with debug symbols
cargo build --profile profiling --bin tpch
samply record ./target/profiling/tpch benchmark datafusion --iterations 5 --path datafusion/benchmarks/data/tpch_sf10 --prefer_hash_join true --format parquet -o datafusion/benchmarks/results/dev2/tpch_sf10.json --query 22
After sampling has completed the Samply starts a local server and navigates to the profiler
Local server listening at http://127.0.0.1:3000
Note: The Firefox profiler cannot be opened in Safari, please use Chrome or Firefox instead